Oral cancer is the 6th most common cancer worldwide. Despite the easy accessibility of the oral cavity for screening, oral cancer has one of the lowest 5-year survival rates of all cancers. Oral cancer is thought to arise as a result of fied cancerization, where, often in response to tobacco and alcohol exposure, wide areas of the mucosal surface develop subclinical carcinogenetic changes. The poor outcomes of oral cancer arise primarily because: (1) most patients are diagnosed at a late stage since the molecular changes that put patients at risk of neoplasia often do not give rise to clinically visible lesions and (2) a large fraction of patients treated for oral cancer develop subsequent cancers because areas of field cancerization persist following treatment and are not clinically visible. The development and progression of oral cancer is ultimately a molecular process, reflecting a complex succession of genetic changes within the field-at-risk. Ultimately tumor-initiating stem cells give rise to aggressive clones within a mucosal field-at-risk, resulting in malignant progression. While much progress has been made to understand the molecular alterations associated with oral cancer progression, this research has not yet led to improvements in early detection mainly because molecular analysis methods are costly and can only be carried out with tissues obtained from invasive biopsies. There is increasing evidence to suggest that key molecular alterations result in phenotypic changes that can be measured clinically at the point-of-care. Recent studies by our group and others suggest that multi-modal optical imaging can image changes in tissue fluorescence and nuclear morphometry to identify high grade oral precancer and early cancer with significantly improved sensitivity and specificity compared to visual examination; moreover, changes in optical properties correlate strongly with molecular markers associated with neoplastic progression. The goal of this proposal is to validate the ability of multimodal optical imaging to improve early detection and to determine whether risk-related optical markers (RROMs) can be used to predict the likelihood of malignant progression. We will perform longitudinal studies in patients with oral lesions using cutting edge autofluorescence and microendoscopy technology with automated diagnostic algorithms. In an animal model of oral cancer, we will combine optical imaging and novel tissue preparation techniques, which render tissue optically transparent and macromolecular permeable, to assess the temporal and spatial correlations of molecular alterations to phenotypic changes during development and progression of oral cancer. With this data, we propose to develop and validate predictive models relating RROMs to malignant transformation.